Importing packages
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import os
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import rawpy
import imageio
import numpy as np
Function swap_channels takes rgb matrix and indices of two channels(x,y) to swap. Returns newly created rgb matrix
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def swap_channels(rgb, x, y):
res = rgb.copy()
x_val = res[:,:,x].copy()
y_val = res[:,:,y].copy()
res[:,:,x] = y_val
res[:,:,y] = x_val
return res
calculate_ndvi - NDVI calculation from rgb matrix
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def calculate_ndvi(rgb):
maxval=np.max(np.max(np.max(rgb)))
bd=255
if maxval>255:
bd= 2**16-1
gamma = 2.2
red = rgb[:, :, 0].copy()
gain = 2
red = gain * (red / bd)**gamma
blue = rgb[:, :, 2].copy()
blue = (blue / bd)**gamma
diff = red - blue
sum_ = blue + red
return np.divide(diff, sum_, out=np.zeros_like(diff), where=sum_!=0)
calculate_lai - LAI calculation from NDVI
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def calculate_lai(ndvi):
return 0.57 * np.exp(2.33 * ndvi)
display_ndvi - Plotting of Ndvi matrix
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def display_ndvi(ndvi, save_path=None):
plt.matshow(ndvi, vmin=-1, vmax=1, cmap=plt.cm.jet)
plt.title("NDVI")
plt.colorbar()
if save_path:
plt.savefig(save_path)
plt.show()
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def display_lai(lai, save_path=None):
plt.matshow(lai, vmin=-1, vmax=1, cmap=plt.cm.jet)
plt.title("LAI")
plt.colorbar()
if save_path:
plt.savefig(save_path)
plt.show()
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def display_spectogram(x, image_name, save_path=None):
plt.specgram(x)
display_image - Plotting image from rgb matrix
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def display_image(rgb):
plt.imshow(rgb)
plt.show()
log_median_rgb - prints channels mean value
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def log_median_rgb(rgb):
def log_channel_median(i, channel_name):
print(f"{channel_name} median value - {np.median(rgb[:, :, i])}")
log_channel_median(0, "Red")
log_channel_median(1, "Green")
log_channel_median(2, "Blue")
display_ndvi_specgram - plotting ndvi spectogram
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def display_ndvi_specgram(ndvi, image_name, save_path = None):
plt.specgram(ndvi.flatten(), Fs=1, vmin=-1, vmax=1)
plt.title(f"Spectogram of {image_name} NDVI")
if save_path:
plt.savefig(save_path)
plt.show()
display_ndvi_psd - displaying psd for ndvi
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def display_ndvi_psd(ndvi, image_name, save_path = None):
plt.psd(ndvi.flatten(), Fs=1)
plt.title(f"Power spectral density of {image_name} NDVI")
if save_path:
plt.savefig(save_path)
plt.show()
get_saving_path - Forming saving path. Used when saving script-generated images to the folder
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def get_saving_path(folder, name, appendix, s_format = "jpg"):
return os.path.join(folder, f"{name}_{appendix}.{s_format}")
work_through_folder - Main function, loops through the input folder, reads all .ARW images, plots image, ouput of green-blue swapping, NDVI. If save_folder parameter was specified, saves the result to output folder
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def work_through_folder(folder, save_folder=None):
for root, _, files in os.walk(folder):
for file in files:
if '.arw' not in file.lower():
continue
path = os.path.join(root, file)
image_name = file.split('.')[0]
print(f"{path} - image")
raw = rawpy.imread(path)
rgb = raw.postprocess(use_camera_wb=True)
swapped = swap_channels(rgb, 1, 2)
ndvi = calculate_ndvi(rgb)
lai = calculate_lai(ndvi)
log_median_rgb(rgb)
display_image(rgb)
display_image(swapped)
ndvi_save_path = None
ndvi_spec_save_path = None
ndvi_psd_save_path = None
lai_spec_save_path = None
if save_folder:
rgb_name = get_saving_path(save_folder, image_name, "rgb")
plt.imsave(rgb_name, rgb)
swapped_name = get_saving_path(save_folder, image_name, "swap")
plt.imsave(swapped_name, swapped)
ndvi_save_path = get_saving_path(save_folder, image_name, "ndvi", "png")
ndvi_spec_save_path = get_saving_path(save_folder, image_name, "ndvi_spectogram", "png")
ndvi_psd_save_path = get_saving_path(save_folder, image_name, "ndvi_psd", "png")
lai_spec_save_path = get_saving_path(save_folder, image_name, "lai", "png")
display_ndvi(ndvi, ndvi_save_path)
display_lai(lai, lai_spec_save_path)
display_ndvi_specgram(ndvi, image_name, ndvi_spec_save_path)
display_ndvi_psd(ndvi, image_name, ndvi_spec_save_path)
Modification of input and output folders
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DATA_FOLDER = "RAW/"
SAVE_FOLDER = "script_output/"
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work_through_folder(DATA_FOLDER, SAVE_FOLDER)
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